From 32654e9651458b59d3a7469b176bf783fdfe9aea Mon Sep 17 00:00:00 2001 From: Gavin Rhys Lloyd Date: Thu, 6 Jul 2023 16:19:12 +0100 Subject: [PATCH] fix documentation due to roxygen no longer needing % to be escaped. - add markdown flag to description file - use text format for citations (includes markdown) - remove % from descriptions (doesnt work with current implementation) --- DESCRIPTION | 1 + R/DFA_class.R | 6 +++--- R/zzz.R | 2 +- man/ANOVA.Rd | 5 ++--- man/DFA.Rd | 5 ++--- man/DatasetExperiment_heatmap.Rd | 5 ++--- man/HCA.Rd | 5 ++--- man/HSD.Rd | 6 +++--- man/HSDEM.Rd | 19 +++++++++---------- man/MTBLS79_DatasetExperiment.Rd | 24 ++++++++++++------------ man/OPLSDA.Rd | 4 ++-- man/OPLSR.Rd | 4 ++-- man/PLSDA.Rd | 18 +++++++++--------- man/PLSR.Rd | 6 +++--- man/SVM.Rd | 13 ++++++------- man/blank_filter.Rd | 8 ++++---- man/corr_coef.Rd | 5 ++--- man/dfa_scores_plot.Rd | 15 +++++++-------- man/dratio_filter.Rd | 8 +++++--- man/filter_by_name.Rd | 4 ++-- man/fold_change.Rd | 8 ++++---- man/fold_change_int.Rd | 8 ++++---- man/fold_change_plot.Rd | 2 +- man/glog_opt_plot.Rd | 8 ++++---- man/glog_transform.Rd | 23 +++++++++++------------ man/hca_dendrogram.Rd | 6 +++--- man/knn_impute.Rd | 8 ++++---- man/linear_model.Rd | 5 ++--- man/mixed_effect.Rd | 24 +++++++++++------------- man/mv_feature_filter.Rd | 10 +++++----- man/mv_sample_filter.Rd | 10 +++++----- man/ontology_cache.Rd | 2 +- man/pls_regcoeff_plot.Rd | 13 ++++++------- man/pls_vip_plot.Rd | 13 ++++++------- man/plsda_feature_importance_plot.Rd | 24 +++++++++++------------- man/plsda_predicted_plot.Rd | 13 ++++++------- man/plsda_roc_plot.Rd | 13 ++++++------- man/pqn_norm.Rd | 8 ++++---- man/rsd_filter.Rd | 8 ++++---- man/sb_corr.Rd | 17 +++++++++-------- man/svm_plot_2d.Rd | 6 +++--- man/tSNE.Rd | 17 +++++++---------- man/tSNE_scatter.Rd | 17 +++++++---------- 43 files changed, 203 insertions(+), 223 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index 5027a6e..82cbde8 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -148,3 +148,4 @@ Suggests: agricolae, VignetteBuilder: knitr biocViews: WorkflowStep, Metabolomics URL: https://github.com/computational-metabolomics/structToolbox +Roxygen: list(markdown = TRUE) diff --git a/R/DFA_class.R b/R/DFA_class.R index 11d5080..bb3cbe8 100644 --- a/R/DFA_class.R +++ b/R/DFA_class.R @@ -230,10 +230,10 @@ dfa_scores_plot = function( ellipse=enum( name = 'Plot ellipses', description=c( - "all" = paste0('Hotelling T2 95\\% ellipses are plotted for all groups and all samples.'), - "group" = 'Hotelling T2 95\\% ellipses are plotted for all groups.', + "all" = 'Hotelling T2 ellipses (p=0.95) are plotted for all groups and all samples.', + "group" = 'Hotelling T2 ellipses (p=0.95) are plotted for all groups.', "none" = 'Ellipses are not included on the plot.', - "sample" = 'A Hotelling T2 95\\% ellipse is plotted for all samples (ignoring group)'), + "sample" = 'A Hotelling T2 ellipse (p=0.95) is plotted for all samples (ignoring group)'), allowed=c('all','group','none','sample'), value='all' ), diff --git a/R/zzz.R b/R/zzz.R index 31926cc..ca7f8b6 100644 --- a/R/zzz.R +++ b/R/zzz.R @@ -26,7 +26,7 @@ get_description=function(id) { cits=citations(M) cits[length(cits)]=NULL for (k in seq_along(cits)) { - cit=format(cits[[k]],style='latex') + cit=format(cits[[k]],style='text') str=c(str,paste0('@references ',cit)) } diff --git a/man/ANOVA.Rd b/man/ANOVA.Rd index f4fe6b4..a592670 100644 --- a/man/ANOVA.Rd +++ b/man/ANOVA.Rd @@ -37,8 +37,7 @@ M = ANOVA(formula=y~Species) M = model_apply(M,D) } \references{ -Fox J, Weisberg S (2019). -\emph{An R Companion to Applied Regression}, Third edition. -Sage, Thousand Oaks CA. +Fox J, Weisberg S (2019). \emph{An R Companion to Applied Regression}, Third +edition. Sage, Thousand Oaks CA. \url{https://socialsciences.mcmaster.ca/jfox/Books/Companion/}. } diff --git a/man/DFA.Rd b/man/DFA.Rd index 0bf7705..1897766 100644 --- a/man/DFA.Rd +++ b/man/DFA.Rd @@ -31,7 +31,6 @@ M = DFA(factor_name='Species') M = model_apply(M,D) } \references{ -Manly B (1986). -\emph{Multivariate Statistical Methods: A Primer}. -Chapman and Hall, Boca Raton. +Manly B (1986). \emph{Multivariate Statistical Methods: A Primer}. Chapman +and Hall, Boca Raton. } diff --git a/man/DatasetExperiment_heatmap.Rd b/man/DatasetExperiment_heatmap.Rd index 96254cf..90d9c52 100644 --- a/man/DatasetExperiment_heatmap.Rd +++ b/man/DatasetExperiment_heatmap.Rd @@ -29,8 +29,7 @@ C = DatasetExperiment_heatmap() chart_plot(C,D) } \references{ -Wickham H (2007). -``Reshaping Data with the reshape Package.'' -\emph{Journal of Statistical Software}, \bold{21}(12), 1--20. +Wickham H (2007). "Reshaping Data with the reshape Package." \emph{Journal +of Statistical Software}, \emph{21}(12), 1-20. \url{http://www.jstatsoft.org/v21/i12/}. } diff --git a/man/HCA.Rd b/man/HCA.Rd index 51947e9..e141b92 100644 --- a/man/HCA.Rd +++ b/man/HCA.Rd @@ -44,8 +44,7 @@ M = model_apply(M,D) } \references{ -R Core Team (2022). -\emph{R: A Language and Environment for Statistical Computing}. -R Foundation for Statistical Computing, Vienna, Austria. +R Core Team (2023). \emph{R: A Language and Environment for Statistical +Computing}. R Foundation for Statistical Computing, Vienna, Austria. \url{https://www.R-project.org/}. } diff --git a/man/HSD.Rd b/man/HSD.Rd index 2a2e08b..a89058d 100644 --- a/man/HSD.Rd +++ b/man/HSD.Rd @@ -39,7 +39,7 @@ M = HSD(formula=y~Species) M = model_apply(M,D) } \references{ -de Mendiburu F (2021). -\emph{agricolae: Statistical Procedures for Agricultural Research}. -R package version 1.3-5, \url{https://CRAN.R-project.org/package=agricolae}. +de Mendiburu F (2023). \emph{agricolae: Statistical Procedures for +Agricultural Research}. R package version 1.3-6, +\url{https://CRAN.R-project.org/package=agricolae}. } diff --git a/man/HSDEM.Rd b/man/HSDEM.Rd index a7670dc..794dca5 100644 --- a/man/HSDEM.Rd +++ b/man/HSDEM.Rd @@ -36,16 +36,15 @@ M = model_apply(M,D) } \references{ -Lenth R (2023). -\emph{emmeans: Estimated Marginal Means, aka Least-Squares Means}. -R package version 1.8.4-1, \url{https://CRAN.R-project.org/package=emmeans}. +Lenth R (2023). \emph{emmeans: Estimated Marginal Means, aka Least-Squares +Means}. R package version 1.8.7, +\url{https://CRAN.R-project.org/package=emmeans}. -Pinheiro J, Bates D, R Core Team (2022). -\emph{nlme: Linear and Nonlinear Mixed Effects Models}. -R package version 3.1-161, \url{https://CRAN.R-project.org/package=nlme}. +Pinheiro J, Bates D, R Core Team (2023). \emph{nlme: Linear and Nonlinear +Mixed Effects Models}. R package version 3.1-162, +\url{https://CRAN.R-project.org/package=nlme}. -Pinheiro JC, Bates DM (2000). -\emph{Mixed-Effects Models in S and S-PLUS}. -Springer, New York. -\Rhref{https://doi.org/10.1007/b98882}{doi:10.1007\slash{}b98882}. +Pinheiro JC, Bates DM (2000). \emph{Mixed-Effects Models in S and S-PLUS}. +Springer, New York. doi:10.1007/b98882 +\url{https://doi.org/10.1007/b98882}. } diff --git a/man/MTBLS79_DatasetExperiment.Rd b/man/MTBLS79_DatasetExperiment.Rd index e4f3453..a55d10b 100644 --- a/man/MTBLS79_DatasetExperiment.Rd +++ b/man/MTBLS79_DatasetExperiment.Rd @@ -7,24 +7,24 @@ MTBLS79_DatasetExperiment(filtered = FALSE) } \arguments{ -\item{filtered}{TRUE to load data with quality control filters already applied, -or FALSE to load the unfiltered data. Default is FALSE. The raw data is available -from (https://www.ebi.ac.uk/metabolights/MTBLS79) and as an R dataset in the +\item{filtered}{TRUE to load data with quality control filters already applied, +or FALSE to load the unfiltered data. Default is FALSE. The raw data is available +from (https://www.ebi.ac.uk/metabolights/MTBLS79) and as an R dataset in the \code{pmp} package, available on Bioconductor.} } \value{ DatasetExperiment object } \description{ -Direct-infusion mass spectrometry (DIMS) metabolomics is an important approach -for characterising molecular responses of organisms to disease, drugs and the -environment. Increasingly large-scale metabolomics studies are being conducted, -necessitating improvements in both bioanalytical and computational workflows -to maintain data quality. This dataset represents a systematic evaluation of -the reproducibility of a multi-batch DIMS metabolomics study of cardiac tissue -extracts. It comprises of twenty biological samples (cow vs. sheep) that were -analysed repeatedly, in 8 batches across 7 days, together with a concurrent set -of quality control (QC) samples. Data are presented from each step of the workflow +Direct-infusion mass spectrometry (DIMS) metabolomics is an important approach +for characterising molecular responses of organisms to disease, drugs and the +environment. Increasingly large-scale metabolomics studies are being conducted, +necessitating improvements in both bioanalytical and computational workflows +to maintain data quality. This dataset represents a systematic evaluation of +the reproducibility of a multi-batch DIMS metabolomics study of cardiac tissue +extracts. It comprises of twenty biological samples (cow vs. sheep) that were +analysed repeatedly, in 8 batches across 7 days, together with a concurrent set +of quality control (QC) samples. Data are presented from each step of the workflow and are available in MetaboLights (https://www.ebi.ac.uk/metabolights/MTBLS79) } \examples{ diff --git a/man/OPLSDA.Rd b/man/OPLSDA.Rd index 9a1e460..dee497f 100644 --- a/man/OPLSDA.Rd +++ b/man/OPLSDA.Rd @@ -22,8 +22,8 @@ A \code{OPLSDA} object with the following \code{output} slots: } } \description{ -OPLS splits a data matrix into two parts. One part - contains information orthogonal to the input vector, and the other is non-orthogonal. +OPLS splits a data matrix into two parts. One part +contains information orthogonal to the input vector, and the other is non-orthogonal. } \examples{ M = OPLSR('number_components'=2,factor_name='Species') diff --git a/man/OPLSR.Rd b/man/OPLSR.Rd index fe2ff6d..c1a2b11 100644 --- a/man/OPLSR.Rd +++ b/man/OPLSR.Rd @@ -22,8 +22,8 @@ A \code{OPLSR} object with the following \code{output} slots: } } \description{ -OPLS splits a data matrix into two parts. One part - contains information orthogonal to the input vector, and the other is non-orthogonal. +OPLS splits a data matrix into two parts. One part +contains information orthogonal to the input vector, and the other is non-orthogonal. } \examples{ M = OPLSR('number_components'=2,factor_name='Species') diff --git a/man/PLSDA.Rd b/man/PLSDA.Rd index 17ec923..2e9a92f 100644 --- a/man/PLSDA.Rd +++ b/man/PLSDA.Rd @@ -41,15 +41,15 @@ This object makes use of functionality from the following packages:\itemize{\ite M = PLSDA('number_components'=2,factor_name='Species') } \references{ -Liland K, Mevik B, Wehrens R (2022). -\emph{pls: Partial Least Squares and Principal Component Regression}. -R package version 2.8-1, \url{https://CRAN.R-project.org/package=pls}. +Liland K, Mevik B, Wehrens R (2023). \emph{pls: Partial Least Squares and +Principal Component Regression}. R package version 2.8-2, +\url{https://CRAN.R-project.org/package=pls}. -Perez NF, Ferre J, Boque R (2009). -``Calculation of the reliability of classification in discriminant partial least-squares binary classification.'' -\emph{Chemometrics and Intelligent Laboratory Systems}, \bold{95}(2), 122-128. +Perez NF, Ferre J, Boque R (2009). "Calculation of the reliability of +classification in discriminant partial least-squares binary +classification." \emph{Chemometrics and Intelligent Laboratory Systems}, +\emph{95}(2), 122-128. -Barker M, Rayens W (2003). -``Partial least squares for discrimination.'' -\emph{Journal of Chemometrics}, \bold{17}(3), 166-173. +Barker M, Rayens W (2003). "Partial least squares for discrimination." +\emph{Journal of Chemometrics}, \emph{17}(3), 166-173. } diff --git a/man/PLSR.Rd b/man/PLSR.Rd index 4272ca1..0fe560b 100644 --- a/man/PLSR.Rd +++ b/man/PLSR.Rd @@ -38,7 +38,7 @@ This object makes use of functionality from the following packages:\itemize{\ite M = PLSR(factor_name='run_order') } \references{ -Liland K, Mevik B, Wehrens R (2022). -\emph{pls: Partial Least Squares and Principal Component Regression}. -R package version 2.8-1, \url{https://CRAN.R-project.org/package=pls}. +Liland K, Mevik B, Wehrens R (2023). \emph{pls: Partial Least Squares and +Principal Component Regression}. R package version 2.8-2, +\url{https://CRAN.R-project.org/package=pls}. } diff --git a/man/SVM.Rd b/man/SVM.Rd index 5cccad1..019174d 100644 --- a/man/SVM.Rd +++ b/man/SVM.Rd @@ -28,7 +28,7 @@ SVM( \item{cost}{(numeric) The cost of violating the constraints. The default is \code{1}.} -\item{class_weights}{(numeric, character, NULL) A named vector of weights for the different classes. Specifying +\item{class_weights}{(numeric, character, NULL) A named vector of weights for the different classes. Specifying "inverse" will choose the weights inversely proportional to the class distribution. The default is \code{NULL}.} \item{...}{Additional slots and values passed to \code{struct_class}.} @@ -55,12 +55,11 @@ This object makes use of functionality from the following packages:\itemize{\ite M = SVM(factor_name='Species',gamma=1) } \references{ -Meyer D, Dimitriadou E, Hornik K, Weingessel A, Leisch F (2022). +Meyer D, Dimitriadou E, Hornik K, Weingessel A, Leisch F (2023). \emph{e1071: Misc Functions of the Department of Statistics, Probability -Theory Group (Formerly: E1071), TU Wien}. -R package version 1.7-12, \url{https://CRAN.R-project.org/package=e1071}. +Theory Group (Formerly: E1071), TU Wien}. R package version 1.7-13, +\url{https://CRAN.R-project.org/package=e1071}. -Brereton RG, Lloyd GR (2010). -``Support Vector Machines for classification and regression.'' -\emph{The Analyst}, \bold{135}(2), 230-267. +Brereton RG, Lloyd GR (2010). "Support Vector Machines for +classification and regression." \emph{The Analyst}, \emph{135}(2), 230-267. } diff --git a/man/blank_filter.Rd b/man/blank_filter.Rd index 663ff39..2704f0c 100644 --- a/man/blank_filter.Rd +++ b/man/blank_filter.Rd @@ -48,8 +48,8 @@ M = blank_filter(fold_change=2, M = model_apply(M,D) } \references{ -Jankevics A, Lloyd GR, Weber RJM (2022). -\emph{pmp: Peak Matrix Processing and signal batch correction for -metabolomics datasets}. -R package version 1.10.0. +Jankevics A, Lloyd GR, Weber RJM (2023). \emph{pmp: Peak Matrix Processing +and signal batch correction for metabolomics datasets}. +doi:10.18129/B9.bioc.pmp \url{https://doi.org/10.18129/B9.bioc.pmp}, R +package version 1.12.0, \url{https://bioconductor.org/packages/pmp}. } diff --git a/man/corr_coef.Rd b/man/corr_coef.Rd index c5b5f04..f67d4b9 100644 --- a/man/corr_coef.Rd +++ b/man/corr_coef.Rd @@ -45,8 +45,7 @@ M = corr_coef(factor_names=c('sample_order','sample_rep')) M = model_apply(M,D) } \references{ -R Core Team (2022). -\emph{R: A Language and Environment for Statistical Computing}. -R Foundation for Statistical Computing, Vienna, Austria. +R Core Team (2023). \emph{R: A Language and Environment for Statistical +Computing}. R Foundation for Statistical Computing, Vienna, Austria. \url{https://www.R-project.org/}. } diff --git a/man/dfa_scores_plot.Rd b/man/dfa_scores_plot.Rd index 4492531..86a6523 100644 --- a/man/dfa_scores_plot.Rd +++ b/man/dfa_scores_plot.Rd @@ -22,7 +22,7 @@ dfa_scores_plot( \item{factor_name}{(character) The name of a sample-meta column to use.} -\item{ellipse}{(character) Plot ellipses. Allowed values are limited to the following: \itemize{\item{\code{"all"}: Hotelling T2 95\% ellipses are plotted for all groups and all samples.}\item{\code{"group"}: Hotelling T2 95\% ellipses are plotted for all groups.}\item{\code{"none"}: Ellipses are not included on the plot.}\item{\code{"sample"}: A Hotelling T2 95\% ellipse is plotted for all samples (ignoring group).}} The default is \code{"all"}.} +\item{ellipse}{(character) Plot ellipses. Allowed values are limited to the following: \itemize{\item{\code{"all"}: Hotelling T2 ellipses (p=0.95) are plotted for all groups and all samples.}\item{\code{"group"}: Hotelling T2 ellipses (p=0.95) are plotted for all groups.}\item{\code{"none"}: Ellipses are not included on the plot.}\item{\code{"sample"}: A Hotelling T2 ellipse (p=0.95) is plotted for all samples (ignoring group).}} The default is \code{"all"}.} \item{label_filter}{(character) Labels are only plotted for the named groups. If zero-length then all groups are included. The default is \code{character(0)}.} @@ -53,12 +53,11 @@ chart_plot(C,M[2]) } \references{ -Wickham H, Seidel D (2022). -\emph{scales: Scale Functions for Visualization}. -R package version 1.2.1, \url{https://CRAN.R-project.org/package=scales}. +Wickham H, Seidel D (2022). \emph{scales: Scale Functions for +Visualization}. R package version 1.2.1, +\url{https://CRAN.R-project.org/package=scales}. -Wickham H (2016). -\emph{ggplot2: Elegant Graphics for Data Analysis}. -Springer-Verlag New York. -ISBN 978-3-319-24277-4, \url{https://ggplot2.tidyverse.org}. +Wickham H (2016). \emph{ggplot2: Elegant Graphics for Data Analysis}. +Springer-Verlag New York. ISBN 978-3-319-24277-4, +\url{https://ggplot2.tidyverse.org}. } diff --git a/man/dratio_filter.Rd b/man/dratio_filter.Rd index a5a43ca..5a4dc2f 100644 --- a/man/dratio_filter.Rd +++ b/man/dratio_filter.Rd @@ -32,7 +32,9 @@ M = dratio_filter(threshold=20,qc_label='QC',factor_name='Class') M = model_apply(M,D) } \references{ -Broadhurst D, Goodacre R, Reinke SN, Kuligowski J, Wilson ID, Lewis MR, Dunn WB (2018). -``Guidelines and considerations for the use of system suitability and quality control samples in mass spectrometry assays applied in untargeted clinical metabolomic studies.'' -\emph{Metabolomics}, \bold{14}(6). +Broadhurst D, Goodacre R, Reinke SN, Kuligowski J, Wilson ID, Lewis MR, +Dunn WB (2018). "Guidelines and considerations for the use of system +suitability and quality control samples in mass spectrometry assays +applied in untargeted clinical metabolomic studies." \emph{Metabolomics}, +\emph{14}(6). } diff --git a/man/filter_by_name.Rd b/man/filter_by_name.Rd index ff3f382..07ac90d 100644 --- a/man/filter_by_name.Rd +++ b/man/filter_by_name.Rd @@ -7,10 +7,10 @@ filter_by_name(mode = "exclude", dimension = "sample", names, ...) } \arguments{ -\item{mode}{"include" or ["exclude"] to subsample a DatasetExperiment by including or +\item{mode}{"include" or \link{"exclude"} to subsample a DatasetExperiment by including or excluding samples/features based on the provided labels} -\item{dimension}{["sample"] or "variable" to filter by sample or feature +\item{dimension}{\link{"sample"} or "variable" to filter by sample or feature labels} \item{names}{the sample/feature identifiers to filter by. Can provide column diff --git a/man/fold_change.Rd b/man/fold_change.Rd index babfb3a..36d9a88 100644 --- a/man/fold_change.Rd +++ b/man/fold_change.Rd @@ -26,7 +26,7 @@ fold_change( \item{control_group}{(character) The level name of the group used in the denominator (where possible) when computing fold change. The default is \code{character(0)}.} -\item{method}{(character) Fold change method. Allowed values are limited to the following: \itemize{\item{\code{"geometric"}: A log transform is applied before using group means to calculate fold change. In the non-tranformedspace this is equivalent to using geometric group means. Confidence intervals for independant and paired sampling are estimated using standard error of the mean in log transformed space before being transformed back to the original space.}\item{\code{"median"}: The group medians and the method described by Price and Bonett[1] is used to estimate confidence intervals. For paired data standard error of the median is used to estimate confidence intervals from the median fold change of all pairs.}\item{\code{"mean"}: The group means and the method described by Price and Bonnet[1] is used to estimate confidence intervals. For paired data standard error of the mean is used to estimate confidence intervals from the mean fold change of all pairs.}} The default is \code{"geometric"}.} +\item{method}{(character) Fold change method. Allowed values are limited to the following: \itemize{\item{\code{"geometric"}: A log transform is applied before using group means to calculate fold change. In the non-tranformedspace this is equivalent to using geometric group means. Confidence intervals for independant and paired sampling are estimated using standard error of the mean in log transformed space before being transformed back to the original space.}\item{\code{"median"}: The group medians and the method described by Price and Bonett\link{1} is used to estimate confidence intervals. For paired data standard error of the median is used to estimate confidence intervals from the median fold change of all pairs.}\item{\code{"mean"}: The group means and the method described by Price and Bonnet\link{1} is used to estimate confidence intervals. For paired data standard error of the mean is used to estimate confidence intervals from the mean fold change of all pairs.}} The default is \code{"geometric"}.} \item{conf_level}{(numeric) The confidence level of the interval. The default is \code{0.95}.} @@ -50,7 +50,7 @@ M = fold_change(factor_name='Class') M = model_apply(M,D) } \references{ -Price Jr RM, Bonett DG (2020). -``Confidence Intervals for Ratios of Means and Medians.'' -\emph{Journal of Educational and Behavioral Statistics}, \bold{45}(6), 750-770. +Price Jr RM, Bonett DG (2020). "Confidence Intervals for Ratios of +Means and Medians." \emph{Journal of Educational and Behavioral Statistics}, +\emph{45}(6), 750-770. } diff --git a/man/fold_change_int.Rd b/man/fold_change_int.Rd index dd48f18..4dff484 100644 --- a/man/fold_change_int.Rd +++ b/man/fold_change_int.Rd @@ -20,7 +20,7 @@ fold_change_int( \item{control_group}{(character) The level names of the groups used in the denominator (where possible) when computing fold change. One level for each factor, assumed to be in the same order as factor_name. The default is \code{character(0)}.} -\item{method}{(character) Fold change method. Allowed values are limited to the following: \itemize{\item{\code{"geometric"}: A log transform is applied before using group means to calculate fold change. In the non-tranformedspace this is equivalent to using geometric group means. Confidence intervals for independant and paired sampling are estimated using standard error of the mean in log transformed space before being transformed back to the original space.}\item{\code{"median"}: The group medians and the method described by Price and Bonett[1] is used to estimate confidence intervals. For paired data standard error of the median is used to estimate confidence intervals from the median fold change of all pairs.}\item{\code{"mean"}: The group means and the method described by Price and Bonnet[1] is used to estimate confidence intervals. For paired data standard error of the mean is used to estimate confidence intervals from the mean fold change of all pairs.}} The default is \code{"geometric"}.} +\item{method}{(character) Fold change method. Allowed values are limited to the following: \itemize{\item{\code{"geometric"}: A log transform is applied before using group means to calculate fold change. In the non-tranformedspace this is equivalent to using geometric group means. Confidence intervals for independant and paired sampling are estimated using standard error of the mean in log transformed space before being transformed back to the original space.}\item{\code{"median"}: The group medians and the method described by Price and Bonett\link{1} is used to estimate confidence intervals. For paired data standard error of the median is used to estimate confidence intervals from the median fold change of all pairs.}\item{\code{"mean"}: The group means and the method described by Price and Bonnet\link{1} is used to estimate confidence intervals. For paired data standard error of the mean is used to estimate confidence intervals from the mean fold change of all pairs.}} The default is \code{"geometric"}.} \item{conf_level}{(numeric) The confidence level of the interval. The default is \code{0.95}.} @@ -46,8 +46,8 @@ M = filter_smeta(mode='exclude',levels='QC',factor_name='Class') + M = model_apply(M,D) } \references{ -Lloyd GR, Jankevics A, Weber RJM (2020). -``struct: an R/Bioconductor-based framework for standardized metabolomics data analysis and beyond.'' -\emph{Bioinformatics}, \bold{36}(22-23), 5551-5552. +Lloyd GR, Jankevics A, Weber RJM (2020). "struct: an +R/Bioconductor-based framework for standardized metabolomics data +analysis and beyond." \emph{Bioinformatics}, \emph{36}(22-23), 5551-5552. \url{https://doi.org/10.1093/bioinformatics/btaa1031}. } diff --git a/man/fold_change_plot.Rd b/man/fold_change_plot.Rd index 7a13485..341d4b3 100644 --- a/man/fold_change_plot.Rd +++ b/man/fold_change_plot.Rd @@ -7,7 +7,7 @@ fold_change_plot(number_features = 20, orientation = "portrait", ...) } \arguments{ -\item{number_features}{(numeric) The number randomly selected features to plot, or +\item{number_features}{(numeric) The number randomly selected features to plot, or a list of column numbers. The default is \code{20}.} \item{orientation}{(character) Plot orientation. Allowed values are limited to the following: \itemize{\item{\code{"landscape"}: Features are plotted on the y-axis.}\item{\code{"portrait"}: Features are plotted on the x-axis.}} The default is \code{"portrait"}.} diff --git a/man/glog_opt_plot.Rd b/man/glog_opt_plot.Rd index 3e08eb8..2d24dad 100644 --- a/man/glog_opt_plot.Rd +++ b/man/glog_opt_plot.Rd @@ -31,8 +31,8 @@ C = glog_opt_plot() chart_plot(C,M,D) } \references{ -Jankevics A, Lloyd GR, Weber RJM (2022). -\emph{pmp: Peak Matrix Processing and signal batch correction for -metabolomics datasets}. -R package version 1.10.0. +Jankevics A, Lloyd GR, Weber RJM (2023). \emph{pmp: Peak Matrix Processing +and signal batch correction for metabolomics datasets}. +doi:10.18129/B9.bioc.pmp \url{https://doi.org/10.18129/B9.bioc.pmp}, R +package version 1.12.0, \url{https://bioconductor.org/packages/pmp}. } diff --git a/man/glog_transform.Rd b/man/glog_transform.Rd index bc90416..1ff25e2 100644 --- a/man/glog_transform.Rd +++ b/man/glog_transform.Rd @@ -34,18 +34,17 @@ M = glog_transform(qc_label='versicolor',factor_name='Species') M = model_apply(M,D) } \references{ -Jankevics A, Lloyd GR, Weber RJM (2022). -\emph{pmp: Peak Matrix Processing and signal batch correction for -metabolomics datasets}. -R package version 1.10.0. +Jankevics A, Lloyd GR, Weber RJM (2023). \emph{pmp: Peak Matrix Processing +and signal batch correction for metabolomics datasets}. +doi:10.18129/B9.bioc.pmp \url{https://doi.org/10.18129/B9.bioc.pmp}, R +package version 1.12.0, \url{https://bioconductor.org/packages/pmp}. -Durbin B, Hardin J, Hawkins D, Rocke D (2002). -``A variance-stabilizing transformation for gene-expression microarray data.'' -\emph{Bioinformatics}, \bold{18}(Suppl 1), S105-S110. +Durbin B, Hardin J, Hawkins D, Rocke D (2002). "A variance-stabilizing +transformation for gene-expression microarray data." \emph{Bioinformatics}, +\emph{18}(Suppl 1), S105-S110. -Parsons HM, Ludwig C, Gunther UL, Viant MR (2007). -``Improved classification accuracy in 1- and ', -'2-dimensional NMR metabolomics data using the variance ', -'stabilising generalised logarithm transformation.'' -\emph{Bioinformatics}, \bold{8}(1), 234. +Parsons HM, Ludwig C, Gunther UL, Viant MR (2007). "Improved +classification accuracy in 1- and ', '2-dimensional NMR metabolomics +data using the variance ', 'stabilising generalised logarithm +transformation." \emph{Bioinformatics}, \emph{8}(1), 234. } diff --git a/man/hca_dendrogram.Rd b/man/hca_dendrogram.Rd index 4dc8620..9e9f676 100644 --- a/man/hca_dendrogram.Rd +++ b/man/hca_dendrogram.Rd @@ -25,7 +25,7 @@ This object makes use of functionality from the following packages:\itemize{\ite C = hca_dendrogram() } \references{ -de Vries A, Ripley BD (2022). -\emph{ggdendro: Create Dendrograms and Tree Diagrams Using 'ggplot2'}. -R package version 0.1.23, \url{https://CRAN.R-project.org/package=ggdendro}. +de Vries A, Ripley BD (2022). \emph{ggdendro: Create Dendrograms and Tree +Diagrams Using 'ggplot2'}. R package version 0.1.23, +\url{https://CRAN.R-project.org/package=ggdendro}. } diff --git a/man/knn_impute.Rd b/man/knn_impute.Rd index 77b4412..98cfd90 100644 --- a/man/knn_impute.Rd +++ b/man/knn_impute.Rd @@ -39,8 +39,8 @@ This object makes use of functionality from the following packages:\itemize{\ite M = knn_impute() } \references{ -Jankevics A, Lloyd GR, Weber RJM (2022). -\emph{pmp: Peak Matrix Processing and signal batch correction for -metabolomics datasets}. -R package version 1.10.0. +Jankevics A, Lloyd GR, Weber RJM (2023). \emph{pmp: Peak Matrix Processing +and signal batch correction for metabolomics datasets}. +doi:10.18129/B9.bioc.pmp \url{https://doi.org/10.18129/B9.bioc.pmp}, R +package version 1.12.0, \url{https://bioconductor.org/packages/pmp}. } diff --git a/man/linear_model.Rd b/man/linear_model.Rd index bf17945..f8f907d 100644 --- a/man/linear_model.Rd +++ b/man/linear_model.Rd @@ -39,8 +39,7 @@ M = linear_model(formula = y~Species) } \references{ -R Core Team (2022). -\emph{R: A Language and Environment for Statistical Computing}. -R Foundation for Statistical Computing, Vienna, Austria. +R Core Team (2023). \emph{R: A Language and Environment for Statistical +Computing}. R Foundation for Statistical Computing, Vienna, Austria. \url{https://www.R-project.org/}. } diff --git a/man/mixed_effect.Rd b/man/mixed_effect.Rd index d331580..da458e4 100644 --- a/man/mixed_effect.Rd +++ b/man/mixed_effect.Rd @@ -38,21 +38,19 @@ M = mixed_effect(formula = y~Species+ Error(id/Species)) M = model_apply(M,D) } \references{ -Pinheiro J, Bates D, R Core Team (2022). -\emph{nlme: Linear and Nonlinear Mixed Effects Models}. -R package version 3.1-161, \url{https://CRAN.R-project.org/package=nlme}. +Pinheiro J, Bates D, R Core Team (2023). \emph{nlme: Linear and Nonlinear +Mixed Effects Models}. R package version 3.1-162, +\url{https://CRAN.R-project.org/package=nlme}. -Pinheiro JC, Bates DM (2000). -\emph{Mixed-Effects Models in S and S-PLUS}. -Springer, New York. -\Rhref{https://doi.org/10.1007/b98882}{doi:10.1007\slash{}b98882}. +Pinheiro JC, Bates DM (2000). \emph{Mixed-Effects Models in S and S-PLUS}. +Springer, New York. doi:10.1007/b98882 +\url{https://doi.org/10.1007/b98882}. -Lenth R (2023). -\emph{emmeans: Estimated Marginal Means, aka Least-Squares Means}. -R package version 1.8.4-1, \url{https://CRAN.R-project.org/package=emmeans}. +Lenth R (2023). \emph{emmeans: Estimated Marginal Means, aka Least-Squares +Means}. R package version 1.8.7, +\url{https://CRAN.R-project.org/package=emmeans}. -Fox J, Weisberg S (2019). -\emph{An R Companion to Applied Regression}, Third edition. -Sage, Thousand Oaks CA. +Fox J, Weisberg S (2019). \emph{An R Companion to Applied Regression}, Third +edition. Sage, Thousand Oaks CA. \url{https://socialsciences.mcmaster.ca/jfox/Books/Companion/}. } diff --git a/man/mv_feature_filter.Rd b/man/mv_feature_filter.Rd index 84618bd..4211e9d 100644 --- a/man/mv_feature_filter.Rd +++ b/man/mv_feature_filter.Rd @@ -27,7 +27,7 @@ mv_feature_filter( A \code{mv_feature_filter} object with the following \code{output} slots: \tabular{ll}{ \code{filtered} \tab (DatasetExperiment) A DatasetExperiment object containing the filtered data. \cr -\code{flags} \tab (data.frame) % missing values and a flag indicating whether the sample was rejected. \cr +\code{flags} \tab (data.frame) \% missing values and a flag indicating whether the sample was rejected. \cr } } \description{ @@ -42,8 +42,8 @@ M = mv_feature_filter(factor_name='Species',qc_label='versicolor') M = model_apply(M,D) } \references{ -Jankevics A, Lloyd GR, Weber RJM (2022). -\emph{pmp: Peak Matrix Processing and signal batch correction for -metabolomics datasets}. -R package version 1.10.0. +Jankevics A, Lloyd GR, Weber RJM (2023). \emph{pmp: Peak Matrix Processing +and signal batch correction for metabolomics datasets}. +doi:10.18129/B9.bioc.pmp \url{https://doi.org/10.18129/B9.bioc.pmp}, R +package version 1.12.0, \url{https://bioconductor.org/packages/pmp}. } diff --git a/man/mv_sample_filter.Rd b/man/mv_sample_filter.Rd index b045334..d74eefa 100644 --- a/man/mv_sample_filter.Rd +++ b/man/mv_sample_filter.Rd @@ -16,7 +16,7 @@ A \code{mv_sample_filter} object with the following \code{output} slots: \tabular{ll}{ \code{filtered} \tab (DatasetExperiment) A DatasetExperiment object containing the filtered data. \cr \code{flags} \tab (data.frame) A flag indicating whether the sample was rejected. 0 = rejected. \cr -\code{percent_missing} \tab (data.frame) % missing values for each sample. \cr +\code{percent_missing} \tab (data.frame) \% missing values for each sample. \cr } } \description{ @@ -29,8 +29,8 @@ This object makes use of functionality from the following packages:\itemize{\ite C = mv_sample_filter() } \references{ -Jankevics A, Lloyd GR, Weber RJM (2022). -\emph{pmp: Peak Matrix Processing and signal batch correction for -metabolomics datasets}. -R package version 1.10.0. +Jankevics A, Lloyd GR, Weber RJM (2023). \emph{pmp: Peak Matrix Processing +and signal batch correction for metabolomics datasets}. +doi:10.18129/B9.bioc.pmp \url{https://doi.org/10.18129/B9.bioc.pmp}, R +package version 1.12.0, \url{https://bioconductor.org/packages/pmp}. } diff --git a/man/ontology_cache.Rd b/man/ontology_cache.Rd index c147f12..4027b0f 100644 --- a/man/ontology_cache.Rd +++ b/man/ontology_cache.Rd @@ -10,7 +10,7 @@ ontology_cache() list of cached ontology terms } \description{ -A cached list of ontology terms obtained from the ontology lookup service +A cached list of ontology terms obtained from the ontology lookup service (OLS) for ontology terms specified for objects in \code{structToolbox}. } \examples{ diff --git a/man/pls_regcoeff_plot.Rd b/man/pls_regcoeff_plot.Rd index 8b504e4..8e30874 100644 --- a/man/pls_regcoeff_plot.Rd +++ b/man/pls_regcoeff_plot.Rd @@ -36,12 +36,11 @@ C = pls_regcoeff_plot(ycol='setosa') chart_plot(C,M[2]) } \references{ -Liland K, Mevik B, Wehrens R (2022). -\emph{pls: Partial Least Squares and Principal Component Regression}. -R package version 2.8-1, \url{https://CRAN.R-project.org/package=pls}. +Liland K, Mevik B, Wehrens R (2023). \emph{pls: Partial Least Squares and +Principal Component Regression}. R package version 2.8-2, +\url{https://CRAN.R-project.org/package=pls}. -Wickham H (2016). -\emph{ggplot2: Elegant Graphics for Data Analysis}. -Springer-Verlag New York. -ISBN 978-3-319-24277-4, \url{https://ggplot2.tidyverse.org}. +Wickham H (2016). \emph{ggplot2: Elegant Graphics for Data Analysis}. +Springer-Verlag New York. ISBN 978-3-319-24277-4, +\url{https://ggplot2.tidyverse.org}. } diff --git a/man/pls_vip_plot.Rd b/man/pls_vip_plot.Rd index 06ee546..439c781 100644 --- a/man/pls_vip_plot.Rd +++ b/man/pls_vip_plot.Rd @@ -34,12 +34,11 @@ C = pls_vip_plot(ycol='setosa') chart_plot(C,M[2]) } \references{ -Liland K, Mevik B, Wehrens R (2022). -\emph{pls: Partial Least Squares and Principal Component Regression}. -R package version 2.8-1, \url{https://CRAN.R-project.org/package=pls}. +Liland K, Mevik B, Wehrens R (2023). \emph{pls: Partial Least Squares and +Principal Component Regression}. R package version 2.8-2, +\url{https://CRAN.R-project.org/package=pls}. -Wickham H (2016). -\emph{ggplot2: Elegant Graphics for Data Analysis}. -Springer-Verlag New York. -ISBN 978-3-319-24277-4, \url{https://ggplot2.tidyverse.org}. +Wickham H (2016). \emph{ggplot2: Elegant Graphics for Data Analysis}. +Springer-Verlag New York. ISBN 978-3-319-24277-4, +\url{https://ggplot2.tidyverse.org}. } diff --git a/man/plsda_feature_importance_plot.Rd b/man/plsda_feature_importance_plot.Rd index 8539971..97777a2 100644 --- a/man/plsda_feature_importance_plot.Rd +++ b/man/plsda_feature_importance_plot.Rd @@ -34,21 +34,19 @@ C = plsda_feature_importance_plot(n_features=30,metric='vip') chart_plot(C,M[2]) } \references{ -Liland K, Mevik B, Wehrens R (2022). -\emph{pls: Partial Least Squares and Principal Component Regression}. -R package version 2.8-1, \url{https://CRAN.R-project.org/package=pls}. +Liland K, Mevik B, Wehrens R (2023). \emph{pls: Partial Least Squares and +Principal Component Regression}. R package version 2.8-2, +\url{https://CRAN.R-project.org/package=pls}. -Wickham H (2016). -\emph{ggplot2: Elegant Graphics for Data Analysis}. -Springer-Verlag New York. -ISBN 978-3-319-24277-4, \url{https://ggplot2.tidyverse.org}. +Wickham H (2016). \emph{ggplot2: Elegant Graphics for Data Analysis}. +Springer-Verlag New York. ISBN 978-3-319-24277-4, +\url{https://ggplot2.tidyverse.org}. -Wickham H (2007). -``Reshaping Data with the reshape Package.'' -\emph{Journal of Statistical Software}, \bold{21}(12), 1--20. +Wickham H (2007). "Reshaping Data with the reshape Package." \emph{Journal +of Statistical Software}, \emph{21}(12), 1-20. \url{http://www.jstatsoft.org/v21/i12/}. -Wilke C (2020). -\emph{cowplot: Streamlined Plot Theme and Plot Annotations for 'ggplot2'}. -R package version 1.1.1, \url{https://CRAN.R-project.org/package=cowplot}. +Wilke C (2020). \emph{cowplot: Streamlined Plot Theme and Plot Annotations +for 'ggplot2'}. R package version 1.1.1, +\url{https://CRAN.R-project.org/package=cowplot}. } diff --git a/man/plsda_predicted_plot.Rd b/man/plsda_predicted_plot.Rd index 8d59834..b3a5deb 100644 --- a/man/plsda_predicted_plot.Rd +++ b/man/plsda_predicted_plot.Rd @@ -36,12 +36,11 @@ C = plsda_predicted_plot(factor_name='Species') chart_plot(C,M[2]) } \references{ -Liland K, Mevik B, Wehrens R (2022). -\emph{pls: Partial Least Squares and Principal Component Regression}. -R package version 2.8-1, \url{https://CRAN.R-project.org/package=pls}. +Liland K, Mevik B, Wehrens R (2023). \emph{pls: Partial Least Squares and +Principal Component Regression}. R package version 2.8-2, +\url{https://CRAN.R-project.org/package=pls}. -Wickham H (2016). -\emph{ggplot2: Elegant Graphics for Data Analysis}. -Springer-Verlag New York. -ISBN 978-3-319-24277-4, \url{https://ggplot2.tidyverse.org}. +Wickham H (2016). \emph{ggplot2: Elegant Graphics for Data Analysis}. +Springer-Verlag New York. ISBN 978-3-319-24277-4, +\url{https://ggplot2.tidyverse.org}. } diff --git a/man/plsda_roc_plot.Rd b/man/plsda_roc_plot.Rd index a111e17..89fc56f 100644 --- a/man/plsda_roc_plot.Rd +++ b/man/plsda_roc_plot.Rd @@ -34,12 +34,11 @@ C = plsda_roc_plot(factor_name='Species') chart_plot(C,M[2]) } \references{ -Liland K, Mevik B, Wehrens R (2022). -\emph{pls: Partial Least Squares and Principal Component Regression}. -R package version 2.8-1, \url{https://CRAN.R-project.org/package=pls}. +Liland K, Mevik B, Wehrens R (2023). \emph{pls: Partial Least Squares and +Principal Component Regression}. R package version 2.8-2, +\url{https://CRAN.R-project.org/package=pls}. -Wickham H (2016). -\emph{ggplot2: Elegant Graphics for Data Analysis}. -Springer-Verlag New York. -ISBN 978-3-319-24277-4, \url{https://ggplot2.tidyverse.org}. +Wickham H (2016). \emph{ggplot2: Elegant Graphics for Data Analysis}. +Springer-Verlag New York. ISBN 978-3-319-24277-4, +\url{https://ggplot2.tidyverse.org}. } diff --git a/man/pqn_norm.Rd b/man/pqn_norm.Rd index 5487ddb..9c0adeb 100644 --- a/man/pqn_norm.Rd +++ b/man/pqn_norm.Rd @@ -49,8 +49,8 @@ M = model_apply(M,D) } \references{ -Jankevics A, Lloyd GR, Weber RJM (2022). -\emph{pmp: Peak Matrix Processing and signal batch correction for -metabolomics datasets}. -R package version 1.10.0. +Jankevics A, Lloyd GR, Weber RJM (2023). \emph{pmp: Peak Matrix Processing +and signal batch correction for metabolomics datasets}. +doi:10.18129/B9.bioc.pmp \url{https://doi.org/10.18129/B9.bioc.pmp}, R +package version 1.12.0, \url{https://bioconductor.org/packages/pmp}. } diff --git a/man/rsd_filter.Rd b/man/rsd_filter.Rd index 57edf54..1750be4 100644 --- a/man/rsd_filter.Rd +++ b/man/rsd_filter.Rd @@ -34,8 +34,8 @@ M = rsd_filter(factor_name='Class') } \references{ -Jankevics A, Lloyd GR, Weber RJM (2022). -\emph{pmp: Peak Matrix Processing and signal batch correction for -metabolomics datasets}. -R package version 1.10.0. +Jankevics A, Lloyd GR, Weber RJM (2023). \emph{pmp: Peak Matrix Processing +and signal batch correction for metabolomics datasets}. +doi:10.18129/B9.bioc.pmp \url{https://doi.org/10.18129/B9.bioc.pmp}, R +package version 1.12.0, \url{https://bioconductor.org/packages/pmp}. } diff --git a/man/sb_corr.Rd b/man/sb_corr.Rd index 2e2f7c3..3db0dac 100644 --- a/man/sb_corr.Rd +++ b/man/sb_corr.Rd @@ -32,7 +32,7 @@ leave-one-out cross-validation. The default is \code{0}.} \item{qc_label}{(character) The label used to identify QC samples. The default is \code{"QC"}.} -\item{spar_lim}{(numeric) A two element vector specifying the upper and lower limits when `spar = 0`. Allows the value of `spar` to be constrained within these limits to prevent overfitting. The default is \code{c(-1.5, 1.5)}.} +\item{spar_lim}{(numeric) A two element vector specifying the upper and lower limits when \code{spar = 0}. Allows the value of \code{spar} to be constrained within these limits to prevent overfitting. The default is \code{c(-1.5, 1.5)}.} \item{...}{Additional slots and values passed to \code{struct_class}.} } @@ -55,12 +55,13 @@ This object makes use of functionality from the following packages:\itemize{\ite M = sb_corr(order_col='run_order',batch_col='batch_no',qc_col='class') } \references{ -Jankevics A, Lloyd GR, Weber RJM (2022). -\emph{pmp: Peak Matrix Processing and signal batch correction for -metabolomics datasets}. -R package version 1.10.0. +Jankevics A, Lloyd GR, Weber RJM (2023). \emph{pmp: Peak Matrix Processing +and signal batch correction for metabolomics datasets}. +doi:10.18129/B9.bioc.pmp \url{https://doi.org/10.18129/B9.bioc.pmp}, R +package version 1.12.0, \url{https://bioconductor.org/packages/pmp}. -Kirwan JA, Broadhurst DI, Davidson RL, Viant MR (2013). -``Characterising and correcting batch variation in an automated direct infusion mass spectrometry (DIMS) metabolomics workflow.'' -\emph{Analytical and Bioanalytical Chemistry}, \bold{405}(15), 5147-5157. +Kirwan JA, Broadhurst DI, Davidson RL, Viant MR (2013). "Characterising +and correcting batch variation in an automated direct infusion mass +spectrometry (DIMS) metabolomics workflow." \emph{Analytical and +Bioanalytical Chemistry}, \emph{405}(15), 5147-5157. } diff --git a/man/svm_plot_2d.Rd b/man/svm_plot_2d.Rd index 5d0396f..07193b3 100644 --- a/man/svm_plot_2d.Rd +++ b/man/svm_plot_2d.Rd @@ -37,8 +37,8 @@ chart_plot(C,M[4],predicted(M[3])) } \references{ -Meyer D, Dimitriadou E, Hornik K, Weingessel A, Leisch F (2022). +Meyer D, Dimitriadou E, Hornik K, Weingessel A, Leisch F (2023). \emph{e1071: Misc Functions of the Department of Statistics, Probability -Theory Group (Formerly: E1071), TU Wien}. -R package version 1.7-12, \url{https://CRAN.R-project.org/package=e1071}. +Theory Group (Formerly: E1071), TU Wien}. R package version 1.7-13, +\url{https://CRAN.R-project.org/package=e1071}. } diff --git a/man/tSNE.Rd b/man/tSNE.Rd index 1491702..72eea79 100644 --- a/man/tSNE.Rd +++ b/man/tSNE.Rd @@ -49,16 +49,13 @@ M = tSNE() } \references{ -van der Maaten L, Hinton G (2008). -``Visualizing High-Dimensional Data Using t-SNE.'' -\emph{Journal of Machine Learning Research}, \bold{9}, 2579-2605. +van der Maaten L, Hinton G (2008). "Visualizing High-Dimensional Data +Using t-SNE." \emph{Journal of Machine Learning Research}, \emph{9}, 2579-2605. -van der Maaten L (2014). -``Accelerating t-SNE using Tree-Based Algorithms.'' -\emph{Journal of Machine Learning Research}, \bold{15}, 3221-3245. +van der Maaten L (2014). "Accelerating t-SNE using Tree-Based +Algorithms." \emph{Journal of Machine Learning Research}, \emph{15}, 3221-3245. -Krijthe JH (2015). -\emph{Rtsne: T-Distributed Stochastic Neighbor Embedding using Barnes-Hut -Implementation}. -R package version 0.16, \url{https://github.com/jkrijthe/Rtsne}. +Krijthe JH (2015). \emph{Rtsne: T-Distributed Stochastic Neighbor Embedding +using Barnes-Hut Implementation}. R package version 0.16, +\url{https://github.com/jkrijthe/Rtsne}. } diff --git a/man/tSNE_scatter.Rd b/man/tSNE_scatter.Rd index d082d4d..e76eec7 100644 --- a/man/tSNE_scatter.Rd +++ b/man/tSNE_scatter.Rd @@ -28,16 +28,13 @@ M = tSNE_scatter(factor_name='Species') } \references{ -van der Maaten L, Hinton G (2008). -``Visualizing High-Dimensional Data Using t-SNE.'' -\emph{Journal of Machine Learning Research}, \bold{9}, 2579-2605. +van der Maaten L, Hinton G (2008). "Visualizing High-Dimensional Data +Using t-SNE." \emph{Journal of Machine Learning Research}, \emph{9}, 2579-2605. -van der Maaten L (2014). -``Accelerating t-SNE using Tree-Based Algorithms.'' -\emph{Journal of Machine Learning Research}, \bold{15}, 3221-3245. +van der Maaten L (2014). "Accelerating t-SNE using Tree-Based +Algorithms." \emph{Journal of Machine Learning Research}, \emph{15}, 3221-3245. -Krijthe JH (2015). -\emph{Rtsne: T-Distributed Stochastic Neighbor Embedding using Barnes-Hut -Implementation}. -R package version 0.16, \url{https://github.com/jkrijthe/Rtsne}. +Krijthe JH (2015). \emph{Rtsne: T-Distributed Stochastic Neighbor Embedding +using Barnes-Hut Implementation}. R package version 0.16, +\url{https://github.com/jkrijthe/Rtsne}. }